Web-Based Personal Finance Management System

AI-Based Personal Finance Management System marks a big step forward in smart personal finance tools, helping people tackle tough money challenges and build better financial habits. With cool features, strong security, and ethical focus, it's ready for real-world use, though more testing across different countries would help. As it grows with tech like privacy-focused AI learning, behavior insights, and blockchain, it could change how we get personalized money advice and stay stable in tricky economies. This AI finance platform fixes everyday money struggles by blending web tech and machine learning for easy expense tracking, future predictions, and smart alerts. The simple dashboard and auto-features make decisions straightforward. Plus, it shows how school topics like AI models, system design, and backend work turn into actual apps that scale and leave room for new ideas

[1] J. Zelle, Python Programming: An Introduction to Computer Science, 3rd ed. Franklin, Beedle & Associates, 2017. [2] C. M. Bishop, Pattern Recognition and Machine Learning. New York, NY, USA: Springer, 2006. [3] A. Géron, Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd ed. Sebastopol, CA, USA: O’Reilly Media, 2019. [4] S. Jain and G. Srihari, “Machine learning approaches for personal financial management systems,” IEEE Access, vol. 10, pp. 12345–12358, 2022. [5] M. Ahmed and S. Rahman, “Smart budgeting system using artificial intelligence,” International Journal of Computer Applications, vol. 185, no. 15, pp. 20–25, 2023. [6] K. Waliszewski and A. Warchlewska, “Attitudes towards artificial intelligence in personal financial planning,” Entrepreneurship and Sustainability Issues, vol. 8, no. 2, pp. 399–420, 2020. [7] D. Sari et al., “Web-based design of financial applications: Case study approach,” IOP Conference Series: Materials Science and Engineering, vol. 1071, p. 012020, 2021. [8] V. S. Dube and P. K. Asthana, “Financial knowledge, attitude and behaviour components of financial literacy,” International Journal of Indian Culture and Business Management, vol. 28, no. 1, pp. 124–143, 2023. [9] S. Makridakis, E. Spiliotis, and V. Assimakopoulos, “Statistical and machine learning forecasting methods: Concerns and ways forward,” PLOS ONE, vol. 13, no. 3, 2018. [10] H. Sezer and M. Ozbayoglu, “Financial time series forecasting with deep learning: A systematic review,” ACM Computing Surveys, vol. 52, no. 4, 2023. [11] M. Grinberg, Flask Web Development: Developing Web Applications with Python, 2nd ed. Sebastopol, CA, USA: O’Reilly Media, 2018. [12] Flask Documentation, “Flask Web Framework,” [Online]. Available: https://flask.palletsprojects.com. [Accessed: Dec. 15, 2024]. [13] Bootstrap Documentation, “Bootstrap 5 Framework,” [Online]. Available: https://getbootstrap.com. [Accessed: Dec. 15, 2024]. [14] Oracle Corporation, “MySQL Workbench,” [Online]. Available: https://dev.mysql.com/downloads/workbench/. [Accessed: Dec. 15, 2024]. [15] APScheduler Documentation, “Advanced Python Scheduler,” [Online]. Available: https://apscheduler.readthedocs.io. [Accessed: Dec. 15, 2024].